Data Equity, Collection, and Disaggregation for Advancing Health Equity

Advancing health equity through rigorous data collection and disaggregation practices Health disparities are frequently masked when data lack disaggregation by race, ethnicity, gender identity, sexual orientation, disability, language, and rurality.Data Equity, Collection, and Disaggregation for Advancing Health Equity synthesizes evolving research, practices, and policies around equitable data collection.It offers a structured approach to closing data gaps that obscure inequities in physical, mental, and emotional health.The book provides recommendations and applied practices for conducting quantitative, qualitative, and mixed methods research through a data equity-informed lens.It addresses methodological challenges including small sample sizes, missing data, data privacy, and the role of artificial intelligence in medical research and practice. Readers will also find: Strategies for strengthening data governance, infrastructure, and systems that support disaggregated collection acro